Adaptive Diagnosis for Transformer With Unknown Faults Based on Antenna-Augmented RFID Sensor and Deep Learning-Reference-Cited by-同舟云学术

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Adaptive Diagnosis for Transformer With Unknown Faults Based on Antenna-Augmented RFID Sensor and Deep Learning

Published:2023-09-01 Issue:17 Volume:23 Page:20423-20436
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wang Tao¹^ORCID,Xiao Yanxia²^ORCID,Li Bing³,He Yigang⁴^ORCID

Affiliation:

1. School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei, China

2. Anhui Heli Company Ltd, Hefei, China

3. School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China

4. School of Electrical Engineering, Wuhan University, Wuhan, China

Funder

National Natural Science Foundation of China

National Key Research and Development Plan “Smart Grid Technology and Equipment”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10235271/10198461.pdf?arnumber=10198461

Reference40 articles.

1. Wavelet sparsity enhancement for extracting transient vibration signatures of bearing structural damages

2. Adaptive fault diagnosis method for rotating machinery with unknown faults under multiple working conditions

3. Fault diagnosis of transformer based on self-powered RFID sensor tag and improved HHT;wang;J Elect Eng Technol,2018

4. ENSEMBLE EMPIRICAL MODE DECOMPOSITION: A NOISE-ASSISTED DATA ANALYSIS METHOD

5. Automatic Pattern Identification Based on the Complex Empirical Mode Decomposition of the Startup Current for the Diagnosis of Rotor Asymmetries in Asynchronous Machines

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